Best Research

Digital surveillance in higher education (HE) is becoming increasingly common, particularly in the context of digital assessments. This research examines the relationships between people and technology, how these relationships impact teaching practices, and the ethical issues that emerge from them. Technologies and human actions are interconnected and can possess inherent biases. Understanding this perspective helps us see how digital surveillance in HE can reinforce power dynamics and may produce unexpected consequences for marginalised groups. Using posthuman methodologies, this approach allows us to explore the complex ways technology and people influence one another. The research aims to provide insights into how assessment technology shapes educational practices and to facilitate discussions about the ethical implications now and in the future through speculative future.

RM's report Learner Experience: Now and Opinions about the Future” discovered: For learners, the future of assessment is digital. 59% of learners prefer digital assessment compared to just 22% for pen & paper. Digital assessment is more attractive to learners than traditional assessments, 64% of learners said they’d be more likely to choose a course if assessed digitally. Digital assessment has changed the learning experience of students positively. There’s a high level of confidence (68%) that learners can be accurately assessed and can better prepare for working in an increasingly digital world with digital assessments. Learners taking professional qualifications are more likely to embrace digital assessment than those taking general qualifications Most Learners want access to digital assessment platforms for up to 2 years before taking high stakes exams digitally. AI & Automation will transform creation and administration of assessments, according to 69% of learners.

This study examines the potential of artificial intelligence in resolving scoring discrepancies in educational assessments, focusing on a guided writing task from a language proficiency test. 1,824 individuals completed a test. From this pool, we identified 50 cases where two human raters exhibited significant disagreement, assigning scores differing by at least 2.5 points out of 10. To investigate AI’s capability in such scenarios, we will compare ChatGPT's scores against a human expert with extensive experience (who resolved the initial conflicts). The study aims to assess AI’s accuracy, reliability, and potential as a tool for standardizing essay evaluation, offering valuable insights into its role in enhancing fairness and consistency in essay scoring.